Scalable, High-Performance, Yarn-Shaped Batteries Activated by an Ultralow Volume of Sweat for Self-Powered Sensing Textiles

One-dimensional sweat-activated batteries (SABs) provide a practical solution to generating electricity for textile electronics due to their excellent flexibility, biocompatibility, and compatibility with conventional textile techniques. However, the low power outputs and slow, inefficient activation during the initial perspiration stage greatly hamper their applications in textile-based, self-powered sensing systems. To address this issue, we developed a core-sheath-structured sweat-activated yarn battery (SAYB) with a Zn-wire core, a cotton-yarn sheath, and an outermost carbon yarn that served as the anode, sweat-wicking separator, and cathode, respectively. The battery has a power density of 1.72 mW cm−2 and an energy capacity of 15.3 mAh, which are much greater than those of the previously reported cotton-yarn-based SAB. The SAYB could be activated by only 1 μL of 100 mM NaCl solution within 3 s, thanks to the thin, hydrophilic cotton sheath, which may shorten the distance and accelerate liquid penetration between the electrodes. The batteries could tolerate 10,000 cycles of bending, 2800 cycles of twisting, and 20 cycles of washing without significantly reducing their power outputs. Multiple batteries connected in proper configurations could power headlights or charge portable gadgets like a smart watch and a smart phone. The SAYB was produced on a large scale (60 m long) to create a sweat-activated energy fabric (5 m long and 0.5 m wide) using conventional weaving techniques. The fabric was further combined with mini wireless analyzers and strain-sensing yarns to prepare a self-powered sensing T-shirt. The T-shirt can be triggered to wirelessly monitor the arm swing frequency and breathing rate in real time after wicking up the sweat created by a volunteer while he is jogging. The SAYBs are expected to contribute to the production of self-powered smart garments for wearable healthcare and exercise monitoring as reliable one-dimensional power sources.